{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Play Dots and Boxes using AlphaZero General.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "machine_shape": "hm"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sDiYgl6eMaWt"
      },
      "source": [
        "# **Setup, install dependencies**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D3HIlAhFE4rt",
        "outputId": "0790a55f-a157-4fbf-d64d-2b22ab702ac7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Clone repo and install requirements\n",
        "\n",
        "!git clone https://github.com/suragnair/alpha-zero-general.git"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'alpha-zero-general'...\n",
            "remote: Enumerating objects: 4, done.\u001b[K\n",
            "remote: Counting objects: 100% (4/4), done.\u001b[K\n",
            "remote: Compressing objects: 100% (4/4), done.\u001b[K\n",
            "remote: Total 1045 (delta 0), reused 3 (delta 0), pack-reused 1041\u001b[K\n",
            "Receiving objects: 100% (1045/1045), 423.63 MiB | 19.50 MiB/s, done.\n",
            "Resolving deltas: 100% (574/574), done.\n",
            "Checking out files: 100% (109/109), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JtAy44ZQbgH_",
        "outputId": "6c0705db-42d4-40f6-f60a-35734edf7132",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "%cd '/content/alpha-zero-general'"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/alpha-zero-general\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FINNt6pobz6u",
        "outputId": "2e471c5c-06d6-42c7-ca47-8b3e226bb6f5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!git checkout -t origin/master"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Branch 'dotsandboxes' set up to track remote branch 'dotsandboxes' from 'origin'.\n",
            "Switched to a new branch 'dotsandboxes'\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q-8kx3_iLSyu",
        "outputId": "68959ad7-bd29-45be-a871-d9ee0f1e4698",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "!pip install -r docker/requirements.txt"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting cffi==1.11.5\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/6d/c0/47db8f624f3e4e2f3f27be03a93379d1ba16a1450a7b1aacfa0366e2c0dd/cffi-1.11.5-cp36-cp36m-manylinux1_x86_64.whl (421kB)\n",
            "\u001b[K     |████████████████████████████████| 430kB 2.8MB/s \n",
            "\u001b[?25hCollecting coloredlogs==14.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/5c/2f/12747be360d6dea432e7b5dfae3419132cb008535cfe614af73b9ce2643b/coloredlogs-14.0-py2.py3-none-any.whl (43kB)\n",
            "\u001b[K     |████████████████████████████████| 51kB 6.2MB/s \n",
            "\u001b[?25hCollecting cython==0.28.3\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/6f/79/d8e2cd00bea8156a995fb284ce7b6677c49eccd2d318f73e201a9ce560dc/Cython-0.28.3-cp36-cp36m-manylinux1_x86_64.whl (3.4MB)\n",
            "\u001b[K     |████████████████████████████████| 3.4MB 12.0MB/s \n",
            "\u001b[?25hCollecting flask==1.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/55/b1/4365193655df97227ace49311365cc296e74b60c7f5c63d23cd30175e2f6/Flask-1.0-py2.py3-none-any.whl (97kB)\n",
            "\u001b[K     |████████████████████████████████| 102kB 10.6MB/s \n",
            "\u001b[?25hCollecting gitpython==2.1.11\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/fe/e5/fafe827507644c32d6dc553a1c435cdf882e0c28918a5bab29f7fbebfb70/GitPython-2.1.11-py2.py3-none-any.whl (448kB)\n",
            "\u001b[K     |████████████████████████████████| 450kB 37.0MB/s \n",
            "\u001b[?25hCollecting matplotlib==2.1.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/34/50/d1649dafaecc91e360b1ca8defebb25f865e29928a98bc7d42ba3b1350e5/matplotlib-2.1.1-cp36-cp36m-manylinux1_x86_64.whl (15.0MB)\n",
            "\u001b[K     |████████████████████████████████| 15.0MB 113kB/s \n",
            "\u001b[?25hCollecting numpy==1.14.5\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/68/1e/116ad560de97694e2d0c1843a7a0075cc9f49e922454d32f49a80eb6f1f2/numpy-1.14.5-cp36-cp36m-manylinux1_x86_64.whl (12.2MB)\n",
            "\u001b[K     |████████████████████████████████| 12.2MB 52.8MB/s \n",
            "\u001b[?25hCollecting pandas==0.23.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/57/eb/6ab533ea8e35e7dd159af6922ac1123d4565d89f3926ad9a6aa46530978f/pandas-0.23.1-cp36-cp36m-manylinux1_x86_64.whl (11.8MB)\n",
            "\u001b[K     |████████████████████████████████| 11.8MB 65.0MB/s \n",
            "\u001b[?25hCollecting scipy==1.1.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/a8/0b/f163da98d3a01b3e0ef1cab8dd2123c34aee2bafbb1c5bffa354cc8a1730/scipy-1.1.0-cp36-cp36m-manylinux1_x86_64.whl (31.2MB)\n",
            "\u001b[K     |████████████████████████████████| 31.2MB 81kB/s \n",
            "\u001b[?25hCollecting scikit-learn==0.19.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/3d/2d/9fbc7baa5f44bc9e88ffb7ed32721b879bfa416573e85031e16f52569bc9/scikit_learn-0.19.1-cp36-cp36m-manylinux1_x86_64.whl (12.4MB)\n",
            "\u001b[K     |████████████████████████████████| 12.4MB 266kB/s \n",
            "\u001b[?25hCollecting scikit-image==0.14.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/34/79/cefff573a53ca3fb4c390739d19541b95f371e24d2990aed4cd8837971f0/scikit_image-0.14.0-cp36-cp36m-manylinux1_x86_64.whl (25.3MB)\n",
            "\u001b[K     |████████████████████████████████| 25.3MB 107kB/s \n",
            "\u001b[?25hCollecting torchfile==0.1.0\n",
            "  Downloading https://files.pythonhosted.org/packages/91/af/5b305f86f2d218091af657ddb53f984ecbd9518ca9fe8ef4103a007252c9/torchfile-0.1.0.tar.gz\n",
            "Collecting torchvision==0.2.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/ca/0d/f00b2885711e08bd71242ebe7b96561e6f6d01fdb4b9dcf4d37e2e13c5e1/torchvision-0.2.1-py2.py3-none-any.whl (54kB)\n",
            "\u001b[K     |████████████████████████████████| 61kB 9.9MB/s \n",
            "\u001b[?25hCollecting tqdm==4.19.5\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/71/3c/341b4fa23cb3abc335207dba057c790f3bb329f6757e1fcd5d347bcf8308/tqdm-4.19.5-py2.py3-none-any.whl (51kB)\n",
            "\u001b[K     |████████████████████████████████| 61kB 9.8MB/s \n",
            "\u001b[?25hCollecting visdom==0.1.7\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/0e/f2/27b5d7c34b718afb355587d4e0c1f9108e925db4c0c932e935ba01051efd/visdom-0.1.7.tar.gz (43kB)\n",
            "\u001b[K     |████████████████████████████████| 51kB 8.3MB/s \n",
            "\u001b[?25hRequirement already satisfied: pycparser in /usr/local/lib/python3.6/dist-packages (from cffi==1.11.5->-r docker/requirements.txt (line 1)) (2.20)\n",
            "Collecting humanfriendly>=7.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/8e/2d/2f1b0a780b8c948c06c74c8c80e68ac354da52397ba432a1c5ac1923c3af/humanfriendly-8.2-py2.py3-none-any.whl (86kB)\n",
            "\u001b[K     |████████████████████████████████| 92kB 12.9MB/s \n",
            "\u001b[?25hRequirement already satisfied: click>=5.1 in /usr/local/lib/python3.6/dist-packages (from flask==1.0->-r docker/requirements.txt (line 4)) (7.1.2)\n",
            "Requirement already satisfied: itsdangerous>=0.24 in /usr/local/lib/python3.6/dist-packages (from flask==1.0->-r docker/requirements.txt (line 4)) (1.1.0)\n",
            "Requirement already satisfied: Werkzeug>=0.14 in /usr/local/lib/python3.6/dist-packages (from flask==1.0->-r docker/requirements.txt (line 4)) (1.0.1)\n",
            "Requirement already satisfied: Jinja2>=2.10 in /usr/local/lib/python3.6/dist-packages (from flask==1.0->-r docker/requirements.txt (line 4)) (2.11.2)\n",
            "Collecting gitdb2>=2.0.0\n",
            "  Downloading https://files.pythonhosted.org/packages/52/7e/59f96b47f671b3fe0aa0c1b609531a540434b719a10c417581e25b383909/gitdb2-4.0.2-py3-none-any.whl\n",
            "Requirement already satisfied: python-dateutil>=2.0 in /usr/local/lib/python3.6/dist-packages (from matplotlib==2.1.1->-r docker/requirements.txt (line 6)) (2.8.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib==2.1.1->-r docker/requirements.txt (line 6)) (0.10.0)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib==2.1.1->-r docker/requirements.txt (line 6)) (2.4.7)\n",
            "Requirement already satisfied: pytz in /usr/local/lib/python3.6/dist-packages (from matplotlib==2.1.1->-r docker/requirements.txt (line 6)) (2018.9)\n",
            "Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib==2.1.1->-r docker/requirements.txt (line 6)) (1.15.0)\n",
            "Requirement already satisfied: dask[array]>=0.9.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image==0.14.0->-r docker/requirements.txt (line 11)) (2.12.0)\n",
            "Requirement already satisfied: PyWavelets>=0.4.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image==0.14.0->-r docker/requirements.txt (line 11)) (1.1.1)\n",
            "Requirement already satisfied: cloudpickle>=0.2.1 in /usr/local/lib/python3.6/dist-packages (from scikit-image==0.14.0->-r docker/requirements.txt (line 11)) (1.3.0)\n",
            "Requirement already satisfied: networkx>=1.8 in /usr/local/lib/python3.6/dist-packages (from scikit-image==0.14.0->-r docker/requirements.txt (line 11)) (2.5)\n",
            "Requirement already satisfied: pillow>=4.3.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image==0.14.0->-r docker/requirements.txt (line 11)) (7.0.0)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.6/dist-packages (from torchvision==0.2.1->-r docker/requirements.txt (line 13)) (1.7.0+cu101)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from visdom==0.1.7->-r docker/requirements.txt (line 15)) (2.23.0)\n",
            "Requirement already satisfied: tornado in /usr/local/lib/python3.6/dist-packages (from visdom==0.1.7->-r docker/requirements.txt (line 15)) (5.1.1)\n",
            "Requirement already satisfied: pyzmq in /usr/local/lib/python3.6/dist-packages (from visdom==0.1.7->-r docker/requirements.txt (line 15)) (19.0.2)\n",
            "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.6/dist-packages (from Jinja2>=2.10->flask==1.0->-r docker/requirements.txt (line 4)) (1.1.1)\n",
            "Collecting gitdb>=4.0.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/48/11/d1800bca0a3bae820b84b7d813ad1eff15a48a64caea9c823fc8c1b119e8/gitdb-4.0.5-py3-none-any.whl (63kB)\n",
            "\u001b[K     |████████████████████████████████| 71kB 11.1MB/s \n",
            "\u001b[?25hRequirement already satisfied: toolz>=0.7.3; extra == \"array\" in /usr/local/lib/python3.6/dist-packages (from dask[array]>=0.9.0->scikit-image==0.14.0->-r docker/requirements.txt (line 11)) (0.11.1)\n",
            "Requirement already satisfied: decorator>=4.3.0 in /usr/local/lib/python3.6/dist-packages (from networkx>=1.8->scikit-image==0.14.0->-r docker/requirements.txt (line 11)) (4.4.2)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from torch->torchvision==0.2.1->-r docker/requirements.txt (line 13)) (0.16.0)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.6/dist-packages (from torch->torchvision==0.2.1->-r docker/requirements.txt (line 13)) (3.7.4.3)\n",
            "Requirement already satisfied: dataclasses in /usr/local/lib/python3.6/dist-packages (from torch->torchvision==0.2.1->-r docker/requirements.txt (line 13)) (0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->visdom==0.1.7->-r docker/requirements.txt (line 15)) (2020.6.20)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->visdom==0.1.7->-r docker/requirements.txt (line 15)) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->visdom==0.1.7->-r docker/requirements.txt (line 15)) (2.10)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->visdom==0.1.7->-r docker/requirements.txt (line 15)) (3.0.4)\n",
            "Collecting smmap<4,>=3.0.1\n",
            "  Downloading https://files.pythonhosted.org/packages/b0/9a/4d409a6234eb940e6a78dfdfc66156e7522262f5f2fecca07dc55915952d/smmap-3.0.4-py2.py3-none-any.whl\n",
            "Building wheels for collected packages: torchfile, visdom\n",
            "  Building wheel for torchfile (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for torchfile: filename=torchfile-0.1.0-cp36-none-any.whl size=5711 sha256=5f0db9c55a17c89973d8bc724490ef0c935ddd88d8451d8928ee072ac86c5fca\n",
            "  Stored in directory: /root/.cache/pip/wheels/b1/c3/d6/9a1cc8f3a99a0fc1124cae20153f36af59a6e683daca0a0814\n",
            "  Building wheel for visdom (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for visdom: filename=visdom-0.1.7-cp36-none-any.whl size=34498 sha256=fa546c6286eb148cb786789aa6729c1936352487f15b953595267971aef4fc68\n",
            "  Stored in directory: /root/.cache/pip/wheels/5c/ea/0f/4e3a4b23f352c708d36d3a7ff654fb014f893f50baa88f2d29\n",
            "Successfully built torchfile visdom\n",
            "\u001b[31mERROR: yellowbrick 0.9.1 has requirement scikit-learn>=0.20, but you'll have scikit-learn 0.19.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: xarray 0.15.1 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: xarray 0.15.1 has requirement pandas>=0.25, but you'll have pandas 0.23.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: umap-learn 0.4.6 has requirement numpy>=1.17, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: umap-learn 0.4.6 has requirement scikit-learn>=0.20, but you'll have scikit-learn 0.19.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: umap-learn 0.4.6 has requirement scipy>=1.3.1, but you'll have scipy 1.1.0 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: tifffile 2020.9.3 has requirement numpy>=1.15.1, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: tensorflow 2.3.0 has requirement numpy<1.19.0,>=1.16.0, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: tensorflow 2.3.0 has requirement scipy==1.4.1, but you'll have scipy 1.1.0 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: spacy 2.2.4 has requirement numpy>=1.15.0, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: spacy 2.2.4 has requirement tqdm<5.0.0,>=4.38.0, but you'll have tqdm 4.19.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: seaborn 0.11.0 has requirement matplotlib>=2.2, but you'll have matplotlib 2.1.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: seaborn 0.11.0 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: rpy2 3.2.7 has requirement cffi>=1.13.1, but you'll have cffi 1.11.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: plotnine 0.6.0 has requirement matplotlib>=3.1.1, but you'll have matplotlib 2.1.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: plotnine 0.6.0 has requirement numpy>=1.16.0, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: plotnine 0.6.0 has requirement pandas>=0.25.0, but you'll have pandas 0.23.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: plotnine 0.6.0 has requirement scipy>=1.2.0, but you'll have scipy 1.1.0 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: numba 0.48.0 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: mizani 0.6.0 has requirement matplotlib>=3.1.1, but you'll have matplotlib 2.1.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: mizani 0.6.0 has requirement pandas>=0.25.0, but you'll have pandas 0.23.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: imgaug 0.2.9 has requirement numpy>=1.15.0, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: imbalanced-learn 0.4.3 has requirement scikit-learn>=0.20, but you'll have scikit-learn 0.19.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: google-colab 1.0.0 has requirement pandas~=1.1.0; python_version >= \"3.0\", but you'll have pandas 0.23.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: fbprophet 0.7.1 has requirement numpy>=1.15.4, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: fbprophet 0.7.1 has requirement pandas>=1.0.4, but you'll have pandas 0.23.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: fbprophet 0.7.1 has requirement tqdm>=4.36.1, but you'll have tqdm 4.19.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: fastai 1.0.61 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: cvxpy 1.0.31 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: blis 0.4.1 has requirement numpy>=1.15.0, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: astropy 4.1 has requirement numpy>=1.16, but you'll have numpy 1.14.5 which is incompatible.\u001b[0m\n",
            "\u001b[31mERROR: albumentations 0.1.12 has requirement imgaug<0.2.7,>=0.2.5, but you'll have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Installing collected packages: cffi, humanfriendly, coloredlogs, cython, flask, smmap, gitdb, gitdb2, gitpython, numpy, matplotlib, pandas, scipy, scikit-learn, scikit-image, torchfile, torchvision, tqdm, visdom\n",
            "  Found existing installation: cffi 1.14.3\n",
            "    Uninstalling cffi-1.14.3:\n",
            "      Successfully uninstalled cffi-1.14.3\n",
            "  Found existing installation: Cython 0.29.21\n",
            "    Uninstalling Cython-0.29.21:\n",
            "      Successfully uninstalled Cython-0.29.21\n",
            "  Found existing installation: Flask 1.1.2\n",
            "    Uninstalling Flask-1.1.2:\n",
            "      Successfully uninstalled Flask-1.1.2\n",
            "  Found existing installation: numpy 1.18.5\n",
            "    Uninstalling numpy-1.18.5:\n",
            "      Successfully uninstalled numpy-1.18.5\n",
            "  Found existing installation: matplotlib 3.2.2\n",
            "    Uninstalling matplotlib-3.2.2:\n",
            "      Successfully uninstalled matplotlib-3.2.2\n",
            "  Found existing installation: pandas 1.1.4\n",
            "    Uninstalling pandas-1.1.4:\n",
            "      Successfully uninstalled pandas-1.1.4\n",
            "  Found existing installation: scipy 1.4.1\n",
            "    Uninstalling scipy-1.4.1:\n",
            "      Successfully uninstalled scipy-1.4.1\n",
            "  Found existing installation: scikit-learn 0.22.2.post1\n",
            "    Uninstalling scikit-learn-0.22.2.post1:\n",
            "      Successfully uninstalled scikit-learn-0.22.2.post1\n",
            "  Found existing installation: scikit-image 0.16.2\n",
            "    Uninstalling scikit-image-0.16.2:\n",
            "      Successfully uninstalled scikit-image-0.16.2\n",
            "  Found existing installation: torchvision 0.8.1+cu101\n",
            "    Uninstalling torchvision-0.8.1+cu101:\n",
            "      Successfully uninstalled torchvision-0.8.1+cu101\n",
            "  Found existing installation: tqdm 4.41.1\n",
            "    Uninstalling tqdm-4.41.1:\n",
            "      Successfully uninstalled tqdm-4.41.1\n",
            "Successfully installed cffi-1.11.5 coloredlogs-14.0 cython-0.28.3 flask-1.0 gitdb-4.0.5 gitdb2-4.0.2 gitpython-2.1.11 humanfriendly-8.2 matplotlib-2.1.1 numpy-1.14.5 pandas-0.23.1 scikit-image-0.14.0 scikit-learn-0.19.1 scipy-1.1.0 smmap-3.0.4 torchfile-0.1.0 torchvision-0.2.1 tqdm-4.19.5 visdom-0.1.7\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "cffi",
                  "matplotlib",
                  "mpl_toolkits",
                  "numpy",
                  "pandas"
                ]
              }
            }
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FJC2hqcSN0NY"
      },
      "source": [
        "# **Instantiate players**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pRpskKggPHAo"
      },
      "source": [
        "import os\n",
        "import numpy as np\n",
        "\n",
        "import Arena\n",
        "from MCTS import MCTS\n",
        "from dotsandboxes.DotsAndBoxesGame import DotsAndBoxesGame\n",
        "from dotsandboxes.DotsAndBoxesPlayers import HumanDotsAndBoxesPlayer, RandomPlayer, GreedyRandomPlayer\n",
        "from dotsandboxes.keras.NNet import NNetWrapper\n",
        "\n",
        "from utils import dotdict"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RJfaPANvQP9N"
      },
      "source": [
        "game = DotsAndBoxesGame(n=3)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Otpq4doZscGN"
      },
      "source": [
        "hp1 = HumanDotsAndBoxesPlayer(game).play\n",
        "hp2 = HumanDotsAndBoxesPlayer(game).play"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3jIWVwA_scvN"
      },
      "source": [
        "rp1 = RandomPlayer(game).play\n",
        "rp2 = RandomPlayer(game).play"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kTfwr_W5se8v"
      },
      "source": [
        "grp1 = GreedyRandomPlayer(game).play\n",
        "grp2 = GreedyRandomPlayer(game).play"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F7g7j_AfNoY3"
      },
      "source": [
        "numMCTSSims = 50"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ufmxe9LOsg5K"
      },
      "source": [
        "nnet1 = NNetWrapper(game)\n",
        "nnet1.load_checkpoint(os.path.join('pretrained_models', 'dotsandboxes', 'keras', '3x3'), 'best.pth.tar')\n",
        "args1 = dotdict({'numMCTSSims': numMCTSSims, 'cpuct': 1.0})\n",
        "mcts1 = MCTS(game, nnet1, args1)\n",
        "alphazero1 = lambda x: np.argmax(mcts1.getActionProb(x, temp=0))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CAijHmg1s1zD"
      },
      "source": [
        "nnet2 = NNetWrapper(game)\n",
        "nnet2.load_checkpoint(os.path.join('pretrained_models', 'dotsandboxes', 'keras', '3x3'), 'best.pth.tar')\n",
        "args2 = dotdict({'numMCTSSims': numMCTSSims, 'cpuct': 1.0})\n",
        "mcts2 = MCTS(game, nnet2, args2)\n",
        "alphazero2 = lambda x: np.argmax(mcts2.getActionProb(x, temp=0))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "33C7jlcEOCDd"
      },
      "source": [
        "# **Play *Random* vs *Greedy Random***\n",
        "\n",
        "*Random* will, as it name says, play all its moves randomly.\n",
        "\n",
        "*Greedy Random* will also play randomly, with the exception that whenever it has the chance to score, it will do that.\n",
        "\n",
        "Let's play 100 games. We expect Greedy Random to win most of the games."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SNH4BFYGtF4a",
        "outputId": "2c0542d8-ba42-4fa1-daae-362be170a498",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Play Random vs Greedy Random\n",
        "player1 = rp1\n",
        "player2 = grp2\n",
        "arena = Arena.Arena(player1, player2, game, display=DotsAndBoxesGame.display)\n",
        "%time oneWon, twoWon, draws = arena.playGames(100, verbose=False)\n",
        "print(\"\\nRandom won {} games, Greedy Random won {} games\".format(oneWon, twoWon))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Arena.playGames (1): 100%|██████████| 50/50 [00:00<00:00, 178.40it/s]\n",
            "Arena.playGames (2): 100%|██████████| 50/50 [00:00<00:00, 172.99it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "CPU times: user 571 ms, sys: 15.4 ms, total: 587 ms\n",
            "Wall time: 573 ms\n",
            "\n",
            "Random won 2 games, Greedy Random won 98 games\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w7yWRruCOvqV"
      },
      "source": [
        "# **Play *Greedy Random* vs *Greedy Random***\n",
        "\n",
        "When both players are Greedy Random, we expect that each wins roughly 50% of the games.\n",
        "\n",
        "Let's play 100 games again."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ufbJfnEps7W8",
        "outputId": "301ce3b7-b62a-4f3b-89b5-1e072bccc629",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Play Greedy Random vs Greedy Random\n",
        "player1 = grp1\n",
        "player2 = grp2\n",
        "arena = Arena.Arena(player1, player2, game, display=DotsAndBoxesGame.display)\n",
        "%time oneWon, twoWon, draws = arena.playGames(100, verbose=False)\n",
        "print(\"\\nGreedy Random #1 won {} games, Greedy Random #2 won {} games\".format(oneWon, twoWon))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Arena.playGames (1): 100%|██████████| 50/50 [00:00<00:00, 131.76it/s]\n",
            "Arena.playGames (2): 100%|██████████| 50/50 [00:00<00:00, 136.39it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "CPU times: user 753 ms, sys: 12.6 ms, total: 765 ms\n",
            "Wall time: 750 ms\n",
            "\n",
            "Greedy Random #1 won 47 games, Greedy Random #2 won 53 games\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h-QS9kRLPWKv"
      },
      "source": [
        "# **Play *Greedy Random* vs *AlphaZero***\n",
        "\n",
        "When both players are Greedy Random, we expect AlphaZero to win most of the games.\n",
        "\n",
        "Let's play 10 games. AlphaZero is considerably slower than GreedyRandom. 10 games will take roughly 2.5 minutes."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1cSmiFO-tjsr",
        "outputId": "4470fd61-5fc7-42b6-9050-9b527e8f5f81",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Play Greedy Random vs AlphaZero\n",
        "player1 = grp1\n",
        "player2 = alphazero1\n",
        "arena = Arena.Arena(player1, player2, game, display=DotsAndBoxesGame.display)\n",
        "%time oneWon, twoWon, draws = arena.playGames(10, verbose=False)\n",
        "print(\"\\nGreedy Random won {} games, Alpha Zero won {} games\".format(oneWon, twoWon))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Arena.playGames (1): 100%|██████████| 5/5 [01:07<00:00, 13.47s/it]\n",
            "Arena.playGames (2): 100%|██████████| 5/5 [01:11<00:00, 14.23s/it]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "CPU times: user 2min 14s, sys: 8.07 s, total: 2min 22s\n",
            "Wall time: 2min 18s\n",
            "\n",
            "Greedy Random won 1 games, Alpha Zero won 9 games\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-9-lgefNW7Xh"
      },
      "source": [
        "# **Play against vs *AlphaZero***\n",
        "\n",
        "Now you can try playing against AlphaZero, you can use the following number guide.\n",
        "You will play one game as the second player and one as the first player.\n",
        "\n",
        "You can also play it directly in this WebApp:\n",
        "\n",
        "https://carlos-aguayo.github.io/alphazero/\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zF6ulqb_XcQ6",
        "outputId": "8977991b-9f52-4e2d-d1c0-7b3b27a1fd55",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        }
      },
      "source": [
        "from IPython.display import Image\n",
        "Image('https://i.imgur.com/qcui7ba.png', width=400)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": [],
            "image/png": {
              "width": 400
            }
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nmKO4YJlSQai",
        "outputId": "2ca0841a-38c5-434d-8f7f-84778778bd8e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Play Greedy Random vs AlphaZero\n",
        "player1 = hp1\n",
        "player2 = alphazero1\n",
        "arena = Arena.Arena(player1, player2, game, display=DotsAndBoxesGame.display)\n",
        "oneWon, twoWon, draws = arena.playGames(2, verbose=True)\n",
        "print(\"You won {} games, Alpha Zero won {} games\".format(oneWon, twoWon))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\rArena.playGames (1):   0%|          | 0/1 [00:00<?, ?it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Turn  1 Player  1\n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Valid moves: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]\n",
            "0\n",
            "Turn  2 Player  -1\n",
            "*-x-*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Turn  3 Player  1\n",
            "*-x-*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Valid moves: [ 1  2  3  4  5  6  7  8  9 10 11 12 14 15 16 17 18 19 20 21 22 23]\n",
            "1\n",
            "Turn  4 Player  -1\n",
            "*-x-*-x-*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Turn  5 Player  1\n",
            "*-x-*-x-*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Valid moves: [ 2  3  4  5  6  7  8  9 10 11 12 14 15 16 17 18 19 20 22 23]\n",
            "2\n",
            "Turn  6 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Turn  7 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "|   x   |   |   \n",
            "*-x-*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Valid moves: [ 4  5  6  7  8  9 10 11 12 14 15 16 17 18 19 20 22 23]\n",
            "12\n",
            "Turn  8 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   |   |   \n",
            "*-x-*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 1.0 x 0.0\n",
            "Turn  9 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   |   |   \n",
            "*-x-*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 1.0 x 0.0\n",
            "Valid moves: [ 4  5  6  7  8  9 10 11 14 15 16 17 18 19 20 22 23]\n",
            "4\n",
            "Turn  10 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   |   |   \n",
            "*-x-*-x-*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 1.0 x 0.0\n",
            "Turn  11 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 1.0 x 1.0\n",
            "Turn  12 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 1.0 x 1.0\n",
            "Turn  13 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 1.0 x 1.0\n",
            "Valid moves: [ 6  7  8  9 10 11 15 16 17 18 19 20 22 23]\n",
            "15\n",
            "Turn  14 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 2.0 x 1.0\n",
            "Turn  15 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 1.0\n",
            "Valid moves: [ 6  7  8  9 10 11 16 17 18 19 20 22 23]\n",
            "6\n",
            "Turn  16 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*---*---*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 1.0\n",
            "Turn  17 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*---*---*\n",
            "|   x   x   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 1.0\n",
            "Valid moves: [ 7  8  9 10 11 16 17 18 19 20 23]\n",
            "7\n",
            "Turn  18 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*---*\n",
            "|   x   x   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 1.0\n",
            "Turn  19 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*---*\n",
            "|   x   x   |   \n",
            "*---*-x-*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 2.0 x 2.0\n",
            "Turn  20 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*---*\n",
            "|   x   x   |   \n",
            "*---*-x-*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 2.0\n",
            "Turn  21 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*---*\n",
            "|   x   x   x   \n",
            "*---*-x-*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 2.0\n",
            "Valid moves: [ 8  9 11 16 17 18 19 20]\n",
            "8\n",
            "Turn  22 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "|   x   x   x   \n",
            "*---*-x-*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 2.0\n",
            "Turn  23 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "|   x   x   x   \n",
            "*---*-x-*-x-*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 2.0 x 3.0\n",
            "Turn  24 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "|   x   x   x   \n",
            "*---*-x-*-x-*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 3.0\n",
            "Turn  25 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*---*-x-*-x-*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 3.0\n",
            "Valid moves: [ 9 16 17 18 19]\n",
            "9\n",
            "Turn  26 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 3.0 x 3.0\n",
            "Turn  27 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 3.0 x 3.0\n",
            "Valid moves: [16 17 18 19]\n",
            "16\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "Arena.playGames (1): 100%|██████████| 1/1 [02:17<00:00, 137.20s/it]\n",
            "Arena.playGames (2):   0%|          | 0/1 [00:00<?, ?it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Turn  28 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 3.0 x 3.0\n",
            "Turn  29 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 3.0 x 4.0\n",
            "Turn  30 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 3.0 x 4.0\n",
            "Turn  31 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 3.0 x 5.0\n",
            "Turn  32 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 3.0 x 5.0\n",
            "Game over: Turn  32 Result  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 3.0 x 6.0\n",
            "Turn  1 Player  1\n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Turn  2 Player  -1\n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Valid moves: [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 17 18 19 20 21 22 23]\n",
            "0\n",
            "Turn  3 Player  1\n",
            "*-x-*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Turn  4 Player  -1\n",
            "*-x-*---*-x-*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Valid moves: [ 1  3  4  5  6  7  8  9 10 11 12 13 14 15 17 18 19 20 21 22 23]\n",
            "1\n",
            "Turn  5 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Turn  6 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "|   x   |   |   \n",
            "*---*---*---*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Valid moves: [ 3  4  5  6  7  8  9 10 11 12 14 15 17 18 19 20 21 22 23]\n",
            "3\n",
            "Turn  7 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "|   x   |   |   \n",
            "*-x-*---*---*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Turn  8 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "|   x   |   |   \n",
            "*-x-*---*-x-*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Valid moves: [ 4  6  7  8  9 10 11 12 14 15 17 18 19 20 21 22 23]\n",
            "4\n",
            "Turn  9 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "|   x   |   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 0.0 x 0.0\n",
            "Turn  10 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "|   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 1.0 x 0.0\n",
            "Turn  11 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "|   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 1.0 x 0.0\n",
            "Turn  12 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 2.0 x 0.0\n",
            "Turn  13 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 2.0 x 0.0\n",
            "Turn  14 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 3.0 x 0.0\n",
            "Turn  15 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   |   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 3.0 x 0.0\n",
            "Turn  16 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   x   |   \n",
            "*---*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 3.0 x 0.0\n",
            "Valid moves: [ 6  7  8  9 10 11 17 19 20 21 22 23]\n",
            "6\n",
            "Turn  17 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   x   |   \n",
            "*-x-*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 3.0 x 0.0\n",
            "Turn  18 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 4.0 x 0.0\n",
            "Turn  19 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*---*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 4.0 x 0.0\n",
            "Turn  20 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 5.0 x 0.0\n",
            "Turn  21 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*---*\n",
            "|   |   |   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 5.0 x 0.0\n",
            "Turn  22 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*---*\n",
            "|   |   x   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 5.0 x 0.0\n",
            "Valid moves: [ 8  9 10 11 19 20 21 23]\n",
            "8\n",
            "Turn  23 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   x   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 5.0 x 0.0\n",
            "Turn  24 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   x   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 6.0 x 0.0\n",
            "Turn  25 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "|   |   x   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 6.0 x 0.0\n",
            "Turn  26 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   x   |   \n",
            "*---*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 6.0 x 0.0\n",
            "Valid moves: [ 9 10 11 21 23]\n",
            "9\n",
            "Turn  27 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   |   x   |   \n",
            "*-x-*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 6.0 x 0.0\n",
            "Turn  28 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*---*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 7.0 x 0.0\n",
            "Turn  29 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*---*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 7.0 x 0.0\n",
            "Turn  30 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*---*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 8.0 x 0.0\n",
            "Turn  31 Player  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*---*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 8.0 x 0.0\n",
            "Turn  32 Player  -1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   |   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 0.0\n",
            "Score 8.0 x 0.0\n",
            "Valid moves: [23]\n",
            "23\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\rArena.playGames (2): 100%|██████████| 1/1 [00:46<00:00, 46.46s/it]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Game over: Turn  32 Result  1\n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "x   x   x   x   \n",
            "*-x-*-x-*-x-*\n",
            "\n",
            "Pass: 1.0\n",
            "Score 8.0 x 1.0\n",
            "\\You won 0 games, Alpha Zero won 2 games\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stderr"
        }
      ]
    }
  ]
}